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Background

The Behavioral Risk Factor Surveillance System (BRFSS) is a collaborative project of the Centers for Disease Control and Prevention (CDC), and U.S. states and territories. The BRFSS, administered and supported by the Behavioral Surveillance Branch (BSB) of the CDC, is an on-going data collection program designed to measure behavioral risk factors in the adult population 18 years of age or over living in households. The BRFSS was initiated in 1984, with 15 states collecting surveillance data on risk behaviors through monthly telephone interviews. The number of states participating in the survey increased, so that by 1998, 50 States, the District of Columbia, Puerto Rico, Guam, and the Virgin Islands were participating in the BRFSS. Oregon has been participating since 1988.

The Behavioral Risk Factor Surveillance System (BRFSS) is a collaborative project of the Centers for Disease Control and Prevention (CDC), and U.S. states and territories. The BRFSS, administered and supported by the Behavioral Surveillance Branch (BSB) of the CDC, is an on-going data collection program designed to measure behavioral risk factors in the adult population 18 years of age or over living in households. The BRFSS was initiated in 1984, with 15 states collecting surveillance data on risk behaviors through monthly telephone interviews. The number of states participating in the survey increased, so that by 1998, 50 States, the District of Columbia, Puerto Rico, Guam, and the Virgin Islands were participating in the BRFSS. Oregon has been participating since 1988.

The objective of the BRFSS is to collect uniform, state-specific data on preventive health practices and risk behaviors that are linked to chronic diseases, injuries, and preventable infectious diseases in the adult population. Factors assessed by the BRFSS include tobacco use, physical activity, dietary practices, safety-belt use, and use of cancer screening services, among others. Data are collected from a random sample of adults (one per household) through a telephone survey.

Health departments use the data for a variety of purposes, including identification of demographic variations in health-related behaviors, targeting services, addressing emergent and critical health issues, proposing legislation for health initiatives and measuring progress toward state and national health objectives.

The health characteristics estimated from the BRFSS pertain only to the adult population age 18 years and older living in households. As noted above, respondents are identified through telephone-based methods. According to the 2000 Census, 98.4 % of Oregon households have telephones. No direct method of compensating for non-telephone coverage is employed by the BRFSS; however, post-stratification weights are used, and these are expected to partially correct for any bias caused by non-telephone coverage. These weights adjust for differences in probability of selection and non-response, as well as non-telephone coverage, and must be used for deriving representative population-based estimates of risk behavior prevalences.

Key Points

The BRFSS collects information from adults on health behaviors and preventive practices related to several leading causes of death.

The BRFSS is used by all states, the District of Columbia, and three territories, through funds disbursed by CDC.

Measuring progress toward achieving state and national health objectives.

The BRFSS gives state health departments a uniform, comprehensive way to monitor selected health behaviors.

The BRFSS can be adapted to meet state-specific needs, while still allowing for state-to-state and regional comparisons.

The BRFSS can be used to assess special populations, such as military personnel and members of health maintenance organizations.

Sample Design

The BRFSS standard for participating area sample designs is that sample records must be justifiable as a probability sample of all households with telephones in the state. Oregon, like the majority of states, uses a disproportionate stratified sample (DSS) design to accomplish this standard.

The DSS design attempts to find a way of differentiating before sampling begins between a set of telephone numbers that contains a large proportion of target numbers, or households (the high-density block) and a set that contains a small proportion of target numbers (the low-density block). The sample of phone numbers are chosen by random digit dial from these stratified sets of phone numbers. In this way, sampling telephone numbers is more efficient compared to simple random sampling.

Until 2002, BRFSS procedures used two groups, referred to as high-density and low-density strata. Whether a telephone number goes into the high-density or low-density stratum is determined by the number of listed household numbers in its hundred block. The hundred block is a set of one hundred telephone numbers with the same area code, prefix, and first two digits of the suffix and all possible combinations of the last two digits. The high-density stratum is sampled at a higher rate than the low-density stratum (that is, disproportionately) to obtain a sample that contains a larger proportion of household numbers than would be the case if all numbers were sampled at the same rate.

In 2002, BRFSS procedures changed to include 3 density strata: low-density, high-density (with expected residential phone numbers), and highest density (with a large percentage of listed numbers in the phone blocks). In 2003, the low-density stratum known as the '0 bank' was dropped from the sample, after review of procedures of many other national surveys, and due to the fact that total numbers of eligible households in these phone banks were decreasing dramatically.

Weighting the data

When data are used without weights, each record counts the same as any other record. Implicit in such use are the assumptions that each record has an equal probability of selection and that non-coverage and non-response are equal among all segments of the population. When deviations from these assumptions are large enough to affect the results obtained from a data set, then weighting each record appropriately can help to adjust for violations of the assumptions. An additional, but conceptually unrelated, reason for weighting is to make the total number of cases equal to some desired number. In the BRFSS, post-stratification serves as a blanket adjustment for non-coverage and non-response and forces the total number of cases to equal population estimates for each geographic stratum, which for the BRFSS is usually a state.

Data Weighting Definition

Data weighting is an important statistical process that attempts to remove bias in the sample.

Purpose

Corrects for differences in the probability of selection due to non-response and non-coverage errors.

Adjusts variables of age, race, and gender between the sample and the entire population.

Allows the generalization of findings to the whole population, not just those who respond to the survey.

Allows comparability of data (to other states, to national data, etc.)

Implications

Design factors affect weighting. In the BRFSS, these factors include:

number of residential telephones in household

number of adults in household

geographic or density stratification

In addition, there is a post-stratification by age and gender that adjusts for non-coverage and non-response and forces the sum of the weighted frequencies to equal population estimates for the state.